AIMC Topic: Image Processing, Computer-Assisted

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Improved cortical surface reconstruction using sub-millimeter resolution MPRAGE by image denoising.

NeuroImage
Automatic cerebral cortical surface reconstruction is a useful tool for cortical anatomy quantification, analysis and visualization. Recently, the Human Connectome Project and several studies have shown the advantages of using T-weighted magnetic res...

Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides.

Medical image analysis
Feature vectors provided by pre-trained deep artificial neural networks have become a dominant source for image representation in recent literature. Their contribution to the performance of image analysis can be improved through fine-tuning. As an ul...

Automated Segmentation of Infarct Lesions in T1-Weighted MRI Scans Using Variational Mode Decomposition and Deep Learning.

Sensors (Basel, Switzerland)
Automated segmentation methods are critical for early detection, prompt actions, and immediate treatments in reducing disability and death risks of brain infarction. This paper aims to develop a fully automated method to segment the infarct lesions f...

Attenuation correction using deep learning for brain perfusion SPECT images.

Annals of nuclear medicine
OBJECTIVE: Non-uniform attenuation correction using computed tomography (CT) improves the image quality and quantification of single-photon emission computed tomography (SPECT). However, it is not widely used because it requires a SPECT/CT scanner. T...

Generative Adversarial Networks to Synthesize Missing T1 and FLAIR MRI Sequences for Use in a Multisequence Brain Tumor Segmentation Model.

Radiology
Background Missing MRI sequences represent an obstacle in the development and use of deep learning (DL) models that require multiple inputs. Purpose To determine if synthesizing brain MRI scans using generative adversarial networks (GANs) allows for ...

Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Performance of blind image quality assessment (BIQA) models has been significantly boosted by end-to-end optimization of feature engineering and quality regression. Nevertheless, due to the distributional shift between images simulated in the laborat...

Batch Coherence-Driven Network for Part-Aware Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Existing part-aware person re-identification methods typically employ two separate steps: namely, body part detection and part-level feature extraction. However, part detection introduces an additional computational cost and is inherently challenging...

A deep learning algorithm proposal to automatic pharyngeal airway detection and segmentation on CBCT images.

Orthodontics & craniofacial research
OBJECTIVES: This study aims to evaluate an automatic segmentation algorithm for pharyngeal airway in cone-beam computed tomography (CBCT) images using a deep learning artificial intelligence (AI) system.

Astrocyte regional heterogeneity revealed through machine learning-based glial neuroanatomical assays.

The Journal of comparative neurology
Evaluation of reactive astrogliosis by neuroanatomical assays represents a common experimental outcome for neuroanatomists. The literature demonstrates several conflicting results as to the accuracy of such measures. We posited that the diverging res...

Artificial intelligence and algorithmic computational pathology: an introduction with renal allograft examples.

Histopathology
Whole slide imaging, which is an important technique in the field of digital pathology, has recently been the subject of increased interest and avenues for utilisation, and with more widespread whole slide image (WSI) utilisation, there will also be ...